Genetics of IgA nephropathy by integrative network-based association studies
基于综合网络关联研究的 IgA 肾病遗传学
基本信息
- 批准号:10660683
- 负责人:
- 金额:$ 68.52万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2015
- 资助国家:美国
- 起止时间:2015-06-17 至 2027-05-31
- 项目状态:未结题
- 来源:
- 关键词:AccelerationAffectAntibodiesAntigen-Antibody ComplexB-Cell Antigen ReceptorBiologicalBiological MarkersBloodBlood VesselsCRISPR/Cas technologyCallbackCandidate Disease GeneCell NucleusCell secretionCellsCharacteristicsChildhoodChromosome MappingCirculationClinicalClinical ResearchComplementComplexDefectDepositionDevelopmentDiseaseDisease ProgressionDisease susceptibilityDrug TargetingEpigenetic ProcessExhibitsFamilyFundingGalactoseGene TargetingGenerationsGenesGeneticGenetic Predisposition to DiseaseGenetic RiskGenomicsGlomerulonephritisGoalsGrantHealthHenoch-Schoenlein PurpuraHeritabilityHeterozygoteHistopathologyHumanIGA GlomerulonephritisIgA receptorIgA1ImmuneImmune systemImmunoglobulin AImmunoglobulinsImmunologicsImmunophenotypingIn VitroIndividualInjury to KidneyIntestinal MucosaJointsKidneyKidney DiseasesKidney FailureKnock-outLigandsMapsMediatingMendelian randomizationMeta-AnalysisModelingMucous MembraneMulticenter StudiesMyeloid CellsNephritisNetwork-basedOutcomePakistanPathogenesisPathogenicityPatientsPharmaceutical PreparationsPhenotypeProspective cohortProteomeRegulatory ElementResolutionRiskRoleSerumSeveritiesSignal TransductionSkinSmall Interfering RNAStudy of serumSusceptibility GeneSystemTherapeutic InterventionTimeValidationVariantVasculitisbiobankcandidate validationcausal variantclinical translationcohortconsanguineous familycytokinedisorder riskendophenotypeexperimental studygain of functiongastrointestinalgenetic analysisgenetic architecturegenetic signaturegenetic variantgenome resourcegenome wide association studygenome-widegenomic locusglycosylationhigh riskinsightinterestloss of functionmultiple omicsnew therapeutic targetnovelphenomepopulation basedprospectivereceptorresponserisk varianttraitvascular inflammationvascular injury
项目摘要
Abstract:
IgA Nephropathy is the most common form of primary glomerulonephritis and an important cause of kidney
failure worldwide. The affected individuals develop characteristic IgA1-containing antibody complexes that
deposit in the kidney, producing progressive renal injury. The disease is associated with a specific pathogenic
defect in the O-glycosylation of IgA1 that promotes formation of immune complexes. Similar to other immune-
mediated disorders, IgA nephropathy has a complex genetic architecture. In the prior funding period, we
completed a GWAS for IgA nephropathy (10,146 cases and 28,751 controls) and we identified 30 genome-
wide significant risk loci, explaining 11% of disease risk. We observed clear convergence of biological
candidate genes on a common set of cytokine ligand-receptor pairs involved in mucosal IgA responses,
including on targets of existing drugs. In a GWAS of 2,170 cases and 5,928 controls, we also defined novel
genome-wide significant loci for IgA vasculitis, a related childhood condition with kidney complications. We
further enhanced these efforts by studies of serum IgA (GWAS in 41,263 individuals) and galactose-deficient-
IgA1 levels (GWAS in 10,193 individuals). Mendelian randomization provided strong genetic support for the
causal role of these endophenotypes. The overall goal of this proposal is to leverage these findings to identify
causal genes underlying shared genetic susceptibility between these traits. In Aim 1, we plan to conduct multi-
phenotype mapping across all four traits to better define shared and trait-specific loci. Multiome single nuclei
sequencing will be used to generate high resolution regulatory maps of IgA+ cells for fine-mapping and
prioritization of candidate causal genes. In Aim 2, we will study the role of the prioritized genes in health and
disease by leveraging Pakistani Genomic Resource, the largest cohort of human knockouts (KOs), with
homozygous KOs for >5000 genes and heterozygous KOs for >18,000 genes. We will perform call-back
studies in selected consanguineous families to identify carriers of loss-of-function and gain-of-function variants
in the genes of interest, followed by clinical and detailed immunophenotyping studies. These efforts will be
complemented by targeted gene perturbation experiments in IgA1-producing cells. In Aim 3, we will perform
phenome-wide association studies, and correlate our new genetic findings with clinical features. Based on
these findings, we will formulate and validate an integrated genomic risk score for kidney disease progression
in two large prospective cohorts of IgA nephropathy and IgA vasculitis with nephritis. These studies are
expected to refine our proposed disease pathogenesis model, define new therapeutic targets, and accelerate
clinical translation of our genetic findings.
抽象的:
IgA肾病是原发性肾小球肾炎最常见的形式,也是肾病的重要病因
全世界的失败。受影响的个体会产生特征性的含有 IgA1 的抗体复合物,
沉积在肾脏,造成进行性肾损伤。该病与特定的致病菌有关
IgA1 的 O-糖基化缺陷促进免疫复合物的形成。与其他免疫类似
IgA 肾病具有复杂的遗传结构。在之前的资助期间,我们
完成了 IgA 肾病的 GWAS(10,146 例病例和 28,751 例对照),我们鉴定了 30 个基因组
广泛的重要风险位点,解释了 11% 的疾病风险。我们观察到生物的明显趋同
参与粘膜 IgA 反应的一组常见细胞因子配体-受体对上的候选基因,
包括现有药物的靶点。在 2,170 个病例和 5,928 个对照的 GWAS 中,我们还定义了新的
IgA 血管炎的全基因组重要位点,这是一种与肾脏并发症相关的儿童疾病。我们
通过对血清 IgA(41,263 名个体的 GWAS)和半乳糖缺乏症的研究进一步加强了这些努力
IgA1 水平(10,193 人的 GWAS)。孟德尔随机化为这一结果提供了强有力的遗传支持
这些内表型的因果作用。该提案的总体目标是利用这些发现来确定
这些性状之间共有遗传易感性的因果基因。在目标 1 中,我们计划开展多项
跨所有四个性状的表型映射,以更好地定义共享和性状特异性基因座。多组单核
测序将用于生成 IgA+ 细胞的高分辨率调控图谱,用于精细绘图和
候选因果基因的优先顺序。在目标 2 中,我们将研究优先基因在健康和
通过利用巴基斯坦基因组资源(最大的人类基因敲除(KO)群体)来治疗疾病
超过 5000 个基因的纯合 KO 和超过 18,000 个基因的杂合 KO。我们将进行回电
在选定的近亲家庭中进行研究,以确定功能丧失和功能获得变异的携带者
感兴趣的基因,然后进行临床和详细的免疫表型研究。这些努力将
并辅之以 IgA1 产生细胞中的靶向基因扰动实验。在目标 3 中,我们将执行
全表组关联研究,并将我们的新遗传发现与临床特征相关联。基于
根据这些发现,我们将制定并验证肾脏疾病进展的综合基因组风险评分
在 IgA 肾病和 IgA 血管炎肾炎的两个大型前瞻性队列中。这些研究是
预计将完善我们提出的疾病发病机制模型,定义新的治疗靶点,并加速
我们的遗传学发现的临床转化。
项目成果
期刊论文数量(4)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
Leukemia Inhibitory Factor Signaling Enhances Production of Galactose-Deficient IgA1 in IgA Nephropathy.
白血病抑制因子信号传导增强 IgA 肾病中半乳糖缺陷型 IgA1 的产生。
- DOI:
- 发表时间:2020-05
- 期刊:
- 影响因子:0
- 作者:Yamada, Koshi;Huang, Zhi Qiang;Raska, Milan;Reily, Colin;Anderson, Joshua C;Suzuki, Hitoshi;Kiryluk, Krzysztof;Gharavi, Ali G;Julian, Bruce A;Willey, Christopher D;Novak, Jan
- 通讯作者:Novak, Jan
Clinical Predictors and Prognosis of Recurrent IgA Nephropathy in the Kidney Allograft.
同种异体肾移植中复发性 IgA 肾病的临床预测因素和预后。
- DOI:
- 发表时间:2022-01
- 期刊:
- 影响因子:0
- 作者:Kavanagh, Catherine R;Zanoni, Francesca;Leal, Rita;Jain, Namrata G;Stack, Megan Nicole;Vasilescu, Elena;Serban, Geo;Shaut, Carley;Kamal, Jeanne;Kudose, Satoru;Martinho, António;Alves, Rui;Santoriello, Dominick;Canetta, Pietro A;Cohen
- 通讯作者:Cohen
Genetic Determinants of IgA Nephropathy: Western Perspective.
IgA 肾病的遗传决定因素:西方观点。
- DOI:10.1016/j.semnephrol.2018.05.014
- 发表时间:2018-09-01
- 期刊:
- 影响因子:3.3
- 作者:Y. Neugut;K. Kiryluk
- 通讯作者:K. Kiryluk
Kidney Failure Risk Prediction Equations in IgA Nephropathy: A Multicenter Risk Assessment Study in Chinese Patients.
IgA 肾病肾衰竭风险预测方程:针对中国患者的多中心风险评估研究。
- DOI:10.1053/j.ajkd.2018.01.043
- 发表时间:2018-09-01
- 期刊:
- 影响因子:0
- 作者:Jingyuan Xie;J. Lv;Weiming Wang;Guisen Li;Zhangsuo Liu;Hongyu Chen;Feifei Xu;Jingru Sun;Ouyang Yan;Xiaoyan Zhang;Meng Yang;Manman Shi;Wen Zhang;H. Ren;K. Kiryluk;Hong Zhang;N. Chen
- 通讯作者:N. Chen
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KRZYSZTOF KIRYLUK的其他文献
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{{ truncateString('KRZYSZTOF KIRYLUK', 18)}}的其他基金
Non-APOL1 genetic factors and kidney transplant outcomes
非 APOL1 遗传因素与肾移植结果
- 批准号:
10717171 - 财政年份:2023
- 资助金额:
$ 68.52万 - 项目类别:
MHC and KIR Sequencing and Association Analyses in the iGeneTRAiN Studies
iGeneTRAiN 研究中的 MHC 和 KIR 测序及关联分析
- 批准号:
10438855 - 财政年份:2020
- 资助金额:
$ 68.52万 - 项目类别:
MHC and KIR Sequencing and Association Analyses in the iGeneTRAiN Studies
iGeneTRAiN 研究中的 MHC 和 KIR 测序及关联分析
- 批准号:
10020606 - 财政年份:2020
- 资助金额:
$ 68.52万 - 项目类别:
MHC and KIR Sequencing and Association Analyses in the iGeneTRAiN Studies
iGeneTRAiN 研究中的 MHC 和 KIR 测序及关联分析
- 批准号:
10251946 - 财政年份:2020
- 资助金额:
$ 68.52万 - 项目类别:
Big Data Methods for Comprehensive Similarity based Risk Prediction
基于大数据的综合相似性风险预测方法
- 批准号:
10087958 - 财政年份:2019
- 资助金额:
$ 68.52万 - 项目类别:
Big Data Methods for Comprehensive Similarity based Risk Prediction
基于大数据的综合相似性风险预测方法
- 批准号:
10323033 - 财政年份:2019
- 资助金额:
$ 68.52万 - 项目类别:
Big Data Methods for Comprehensive Similarity based Risk Prediction
基于大数据的综合相似性风险预测方法
- 批准号:
10551349 - 财政年份:2019
- 资助金额:
$ 68.52万 - 项目类别:
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